Vehicle accidents are known to occur when a driver becomes drowsy, distracted, or generally lacks awareness. In an attempt to anticipate driver drowsiness and/or distraction, known video monitoring systems include one or two cameras focused on the driver of the vehicle to capture images of the driver's facial characteristics which are indicative of the driver's state. Such facial characteristics include the position, orientation, and movement of the driver's head, eye position and gaze, and ocular data. By recognizing the driver's facial characteristics, vehicle control systems can provide enhanced vehicle functions and possibly reduce the risks of driver induced accidents.
For example, one such system is disclosed in U.S. Pat. No. 6,859,144, issued Feb. 22, 2005, assigned to the Assignee of the present invention and incorporated herein by reference in its entirety. In this system, a potential vehicle situation is determined by two video cameras sensing eye gaze direction of the driver and comparing this data with other data stored in memory of a system processor/controller. On the basis of this comparison, various automated vehicle alert actions can be taken. This system is limited to eye gaze and, unfortunately, other facial characteristics (e.g. head pose) that greatly contribute in determining driver state are essentially ignored. Yet further, to measure direction of eye gaze the processor algorithms require at least two cameras for reliable determination, which is costly.
Known head pose algorithms typically apply three angles representing deviations from a nominal pose. Two cameras have traditionally been required so that the three dimensional components of the head pose (or in this instance the eye gaze) can be reliably calculated from the stereo information about the eyes.
Another example of a driver state monitoring system is disclosed in U.S. Patent Application Publication 2004/0090334, filed Nov. 11, 2002, assigned to the Assignee of the present invention and incorporated herein by reference in its entirety. This system is relatively low cost because it requires only one camera. This system generally is capable of detecting only drowsiness and by only measuring a temporal percentage of eye closure. That is, the system does not measure any type of three-dimensional head pose (i.e. nodding of the head which is an indicator of drowsiness), and instead, relies upon a processor to determine a time proportion of eye closure versus non-closure and compares the time proportion against a pre-established threshold value.